171 citations · 386 across the 30 of their papers we have counts for
6 papers · 2 filters
PACT: Perception-Action Causal Transformer for Autoregressive Robotics Pre-Training
Rogerio Bonatti, Sai Vemprala, Shuang Ma +3
Robotics has long been a field riddled with complex systems architectures whose modules and connections, whether traditional or learning-based, require significant human expertise…
Learning to Simulate Realistic LiDARs
Benoit Guillard, Sai Vemprala, Jayesh K. Gupta +4
Simulating realistic sensors is a challenging part in data generation for autonomous systems, often involving carefully handcrafted sensor design, scene properties, and physics mod…
LATTE: LAnguage Trajectory TransformEr
Arthur Bucker, Luis Figueredo, Sami Haddadin +4
Natural language is one of the most intuitive ways to express human intent. However, translating instructions and commands towards robotic motion generation and deployment in the r…
Sample-efficient Safe Learning for Online Nonlinear Control with Control Barrier Functions
Wenhao Luo, Wen Sun, Ashish Kapoor
Reinforcement Learning (RL) and continuous nonlinear control have been successfully deployed in multiple domains of complicated sequential decision-making tasks. However, given the…
Reshaping Robot Trajectories Using Natural Language Commands: A Study of Multi-Modal Data Alignment Using Transformers
Arthur Bucker, Luis Figueredo, Sami Haddadin +3
Natural language is the most intuitive medium for us to interact with other people when expressing commands and instructions. However, using language is seldom an easy task when hu…
COMPASS: Contrastive Multimodal Pretraining for Autonomous Systems
Shuang Ma, Sai Vemprala, Wenshan Wang +4
Learning representations that generalize across tasks and domains is challenging yet necessary for autonomous systems. Although task-driven approaches are appealing, designing mode…